Diseño de un agente inteligente basado en una red neuronal artificial supervisada. Validación en un dominio botánico
Artificial Neural Networks (ANN) were created to simulate the components and functions of the human brain. The properties of ANN enable problems apply in pattern recognition and classification, as they are able to discover no apparent relationships between variables, and both give meaning to data. A...
Guardado en:
| Autores principales: | , |
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| Formato: | Artículo revista |
| Lenguaje: | Español |
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Escuela de Perfeccionamiento en Investigación Operativa
2021
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/epio/article/view/33195 |
| Aporte de: |
| Sumario: | Artificial Neural Networks (ANN) were created to simulate the components and functions of the human brain. The properties of ANN enable problems apply in pattern recognition and classification, as they are able to discover no apparent relationships between variables, and both give meaning to data. An intelligent agent whose performance is monitored element models of RNA is described. Validation was applied to the automatic identification of three plant species of Rollinia: R. salicifolia, R. emarginata and R. rugulosa. The constructed and validated models are presented, and the one selected from the best results obtained by evaluating the Mean Square Error and the percentage of errors, this was incorporated into the intelligent agent. The agent consists of a user interface to ensure its use. The proposal may be adapted to other knowledge’s domains. |
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